Abstract Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in
industry and business practice, while management-oriented research disciplines seem …

Big social data and user-generated content have emerged as important sources of timely
and rich knowledge to detect customers' behavioral patterns. Revealing customer …

Text clustering is one of the most commonly used methods for detecting themes or types of
documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to …

The image is an important way for people to understand the world. How to make the
computer have image recognition function is the goal of image recognition research. In …

Due to its simplicity and intuitive interpretability, spherical k-means is often used for
clustering a large number of documents. However, there exist a number of drawbacks that …

With the rapid development of web technology, the social networks have become the largest
information portals. In the social platforms, the text information can effectively reflect the user …

Efficient big data clustering is a requirement for massive data generating in this digitalized
connected world. The traditional clustering algorithms do not scale over massively sized and …

Big data analysis and mining aims to discover implicit, previously unknown, and potentially
useful information and knowledge from big databases that contain high volumes of valuable …

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to
keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper …

Lithology identification is an important part of reservoir evaluation and reservoir description
when processing and interpreting geophysical record data. Clustering analysis refers to the …